Comparison of the within-reader and inter-vendor agreement of left ventricular circumferential strains and volume indices derived from cardiovascular magnetic resonance imaging

Role of CT and CMR in the Management of Chronic Coronary Syndrome

Chronic coronary syndrome (CCS), encompassing a wide range of phenotypes and clinical scenarios, remains the leading global cause of disability and premature death. Advanced non-invasive imaging modalities, such as coronary computed tomography angiography (CCTA) and cardiac magnetic resonance (CMR), play a pivotal role in enhancing diagnostic accuracy and guiding tailored management strategies for CCS patients. CCTA offers detailed insights into the presence, extent, and severity of coronary atherosclerotic plaques. In addition to detecting coronary stenoses, it enables the characterization of plaque phenotypes and the evaluation of additional prognostic biomarkers, such as perivascular adipose tissue (PVAT) attenuation, allowing for more comprehensive risk stratification. Recent technological advancements have further expanded CCTA's capabilities, enabling the integration of anatomical assessment with hemodynamic evaluation through non-invasive fractional flow reserve computation (FFR-CT) or stress myocardial perfusion analysis. With its superior three-dimensional spatial resolution, CCTA enhances pre-procedural planning for complex coronary revascularization, enabling the selection of optimal interventional strategies and improving patient selection. CMR is considered the gold standard for functional assessment of cardiac function, myocardial viability, quantitative flow evaluation, and tissue characterization, offering excellent soft-tissue contrast. CMR perfusion imaging can accurately assess myocardial ischemia, quantify myocardial blood flow (MBF), and detect microvascular dysfunction, thanks to its high temporal and spatial resolution with the advantage of no radiation exposure. This review highlights the evolving role of CCTA and CMR in managing patients with CCS, focusing on their current applications according to the most recent 2024 ESC guidelines, prognostic value, and recent technological advancements.

Cardiac magnetic resonance in advanced heart failure

Heart failure (HF) is a chronic and progressive disease that often progresses to an advanced stage where conventional therapy is insufficient to relieve patients' symptoms. Despite the availability of advanced therapies such as mechanical circulatory support or heart transplantation, the complexity of defining advanced HF, which requires multiple parameters and multimodality assessment, often leads to delays in referral to dedicated specialists with the result of a worsening prognosis. In this review, we aim to explore the role of cardiac magnetic resonance (CMR) in advanced HF by showing how CMR is useful at every step in managing these patients: from diagnosis to prognostic stratification, hemodynamic evaluation, follow-up and advanced therapies such as heart transplantation. The technical challenges of scanning advanced HF patients, which often require troubleshooting of intracardiac devices and dedicated scans, will be also discussed.

Reproducibility of Left Ventricular Function Derived From Cardiac Magnetic Resonance and Gated 13N-Ammonia Positron Emission Tomography Myocardial Perfusion Imaging: A Head-to-Head Comparison Using Hybrid Positron Emission Tomography/Magnetic Resonance

RATIONALE AND OBJECTIVES

Cardiac magnetic resonance (CMR) and gated 13N-ammonia positron emission tomography myocardial perfusion imaging (PET-MPI) offer accurate and highly comparable global left ventricular ejection fraction (LVEF) measurements. In addition to accuracy, however, reproducibility is crucial to avoid variations in LVEF assessment potentially negatively impacting treatment decisions. We performed a head-to-head comparison of the reproducibility of LVEF measurements derived from simultaneously acquired CMR and PET-MPI using different state-of-the-art commercially available software.

MATERIALS AND METHODS

93 patients undergoing hybrid PET/MR were retrospectively included. LVEF was derived from CMR and PET-MPI at two separate core labs, using two state-of-the-art software packages for CMR (cvi42 and Medis Suite MR) and PET (QPET and CardIQ Physio). Intra- and inter-reader agreement was assessed using correlation and Bland-Altman (BA) analyses.

RESULTS

While intra- and inter-reader reproducibility of LVEF was high among both modalities and all software packages (r ≥ 0.87 and ICC≥0.91, all significant at p < 0.0001), LVEF derived from PET-MPI and analyzed with QPET outperformed all other analyses (intra-reader reproducibility: r = 0.99, ICC=0.99; inter-reader reproducibility: r = 0.98, ICC=1.00; Pearson correlations significantly higher than all others at p ≤ 0.0001). BA analyses showed smaller biases for LVEF derived from PET-MPI (-0.1% and +0.9% for intra-reader, -0.4% and -0.8% for inter-reader agreement) than those derived from CMR (+0.7% and +2.8% for intra-reader, -0.9% and -2.2% for inter-reader agreement) with similar results for BA limits of agreement.

CONCLUSION

Gated 13N-ammonia PET-MPI provides equivalent reproducibility of LVEF compared to CMR. It may offer a valid alternative to CMR for patients requiring LV functional assessment.

Deep learning automates detection of wall motion abnormalities via measurement of longitudinal strain from ECG-gated CT images

Introduction

4D cardiac CT (cineCT) is increasingly used to evaluate cardiac dynamics. While echocardiography and CMR have demonstrated the utility of longitudinal strain (LS) measures, measuring LS from cineCT currently requires reformatting the 4D dataset into long-axis imaging planes and delineating the endocardial boundary across time. In this work, we demonstrate the ability of a recently published deep learning framework to automatically and accurately measure LS for detection of wall motion abnormalities (WMA).

Methods

One hundred clinical cineCT studies were evaluated by three experienced cardiac CT readers to identify whether each AHA segment had a WMA. Fifty cases were used for method development and an independent group of 50 were used for testing. A previously developed convolutional neural network was used to automatically segment the LV bloodpool and to define the 2, 3, and 4 CH long-axis imaging planes. LS was measured as the perimeter of the bloodpool for each long-axis plane. Two smoothing approaches were developed to avoid artifacts due to papillary muscle insertion and texture of the endocardial surface. The impact of the smoothing was evaluated by comparison of LS estimates to LV ejection fraction and the fractional area change of the corresponding view.

Results

The automated, DL approach successfully analyzed 48/50 patients in the training cohort and 47/50 in the testing cohort. The optimal LS cutoff for identification of WMA was -21.8, -15.4, and -16.6% for the 2-, 3-, and 4-CH views in the training cohort. This led to correct labeling of 85, 85, and 83% of 2-, 3-, and 4-CH views, respectively, in the testing cohort. Per-study accuracy was 83% (84% sensitivity and 82% specificity). Smoothing significantly improved agreement between LS and fractional area change (R 2: 2 CH = 0.38 vs. 0.89 vs. 0.92).

Conclusion

Automated LV blood pool segmentation and long-axis plane delineation via deep learning enables automatic LS assessment. LS values accurately identify regional wall motion abnormalities and may be used to complement standard visual assessments.

Acute regional changes in myocardial strain may predict ventricular remodelling after myocardial infarction in a large animal model

To identify predictors of left ventricular remodelling (LVR) post-myocardial infarction (MI) and related molecular signatures, a porcine model of closed-chest balloon MI was used along with serial cardiac magnetic resonance imaging (CMRI) up to 5-6 weeks post-MI. Changes in myocardial strain and strain rates were derived from CMRI data. Tissue proteomics was compared between infarcted and non-infarcted territories. Peak values of left ventricular (LV) apical circumferential strain (ACS) changed over time together with peak global circumferential strain (GCS) while peak GLS epicardial strains or strain rates did not change over time. Early LVR post-MI enhanced abundance of 39 proteins in infarcted LV territories, 21 of which correlated with LV equatorial circumferential strain rate. The strongest associations were observed for D-3-phosphoglycerate dehydrogenase (D-3PGDH), cysteine and glycine-rich protein-2, and secreted frizzled-related protein 1 (sFRP1). This study shows that early changes in regional peak ACS persist at 5-6 weeks post-MI, when early LVR is observed along with increased tissue levels of D-3PGDH and sFRP1. More studies are needed to ascertain if the observed increase in tissue levels of D-3PGDH and sFRP1 might be casually involved in the pathogenesis of adverse LV remodelling.